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  4. Integrated use of remote sensing, GIS and precipitation data for the assessment of soil erosion rate in the catchment area of “Yialias” in Cyprus
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Integrated use of remote sensing, GIS and precipitation data for the assessment of soil erosion rate in the catchment area of “Yialias” in Cyprus

Journal
Atmospheric Research
Date Issued
September 2013
Author(s)
Alexakis, Dimitrios  
Hadjimitsis, Diofantos G.  
Agapiou, Athos  
DOI
10.1016/j.atmosres.2013.02.013
Abstract
he objective of this work is to develop an overall methodology for estimating erosion rate in a catchment area in Cyprus with the integrated use of satellite remote sensing (RS), Geographical Information Systems (GIS) and precipitation data. Two models were implemented in a river basin in the central part of Cyprus (Yialias River) which is generally prone to erosion processes. The first is a quantitative empirical multi-parametric model which is based both in expert's knowledge and Analytical Hierarchical Process (AHP) while the second is the Revised Universal Soil Loss Equation (RUSLE) model which is considered to be a contemporary approach in soil loss assessment. For the implementation of the two different models, high resolution GeoEye-1 satellite images were used in order to extract land cover, soil and topographical information regarding the study area. RUSLE method is based in the estimation of soil loss per unit area and takes into account specific parameters such as precipitation data, topography, soil erodibility, erosivity and runoff. The RUSLE factors were calculated in GIS environment. On the other hand AHP method contributed to the construction of a risk assessment map with the use of almost the same agents with RUSLE methodology. RUSLE and AHP approaches were compared and evaluated for their efficiency.
The study indicated that using RS and GIS technologies simultaneously with precipitation data resulted to an effective and accurate assessment of soil erosion in considerable short time and low cost for large watersheds.
Subjects

Erosion

GIS

Remote sensing

RUSLE

AHP

Cyprus

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